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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…This fact has proven the robustness of genetic algorithm itself. Alongside the fluctuation studies, this paper also presents the results of standard deviation and 95 confidence interval calculations towards the true mean of best solutions' fitness values. …”
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  4. 4
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…This fact has proven the robustness of genetic algorithm itself. Alongside the fluctuation studies, this paper also presents the results of standard deviation and 95 confidence interval calculations towards the true mean of best solutions' fitness values. …”
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  5. 5
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  6. 6
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  7. 7
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  8. 8
    Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm

    Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Jianghua Yin, Jianghua Yin, Guodong Ma, Guodong Ma

    Published 2023
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  9. 9
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  10. 10
    Incremental interval type-2 fuzzy clustering of data streams using single pass method

    Incremental interval type-2 fuzzy clustering of data streams using single pass method by Qaiyum, S., Aziz, I., Hasan, M.H., Khan, A.I., Almalawi, A.

    Published 2020
    “…Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). …”
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  11. 11
    Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts

    Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts by Ng Peh, Sang

    Published 2020
    “…The first objective of this thesis is to develop the run sum X - AI (RS X - AI) chart for monitoring the process mean. Optimal parameters computed using the optimization algorithms developed and the step-by-step approach for constructing the optimal RS - AI chart are provided in this thesis. …”
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  12. 12
    Forecasting solar power generation using evolutionary mating algorithm-deep neural networks

    Forecasting solar power generation using evolutionary mating algorithm-deep neural networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…Additionally, the paper conducts a comprehensive comparison with established algorithms, including Differential Evolution (DE-DNN), Barnacles Mating Optimizer (BMO-DNN), Particle Swarm Optimization (PSO-DNN), Harmony Search Algorithm (HSA-DNN), DNN with Adaptive Moment Estimation optimizer (ADAM) and Nonlinear AutoRegressive with eXogenous inputs (NARX). …”
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  13. 13
    Optimization of super twisting sliding mode control gains using Taguchi method

    Optimization of super twisting sliding mode control gains using Taguchi method by Jamaludin, Zamberi, Chiew, Tsung Heng, Bani Hashim, Ahmad Yusairi, Rafan, Nur Aidawaty, Abdullah, Lokman

    Published 2018
    “…Optimized algorithm achieved 9.3% of reduction in root mean square of tracking error and 38.4% of reduction in chattering experimentally.…”
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  14. 14
    A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus

    A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus by Megat Yunus, Puteri Nor Ashikin

    Published 2023
    “…After that, a hybrid of MLFNN with other optimization methods was introduced, i.e. Improved Fast Evolutionary Programming (IFEP), Evolutionary Programming- Dolphin Echolocation Algorithm (EPDEA) and Evolutionary Programming-Firefly Algorithm (EPFA). …”
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  15. 15
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The RUL prediction results with uncertainty quantification at a 95 % confidence interval (CI) are also analyzed. The findings indicate that the proposed LSA + LSTM model, outperforms other optimization-based LSTM models in predictive accuracy, attaining a minimum Root Mean Square Error (RMSE) of 0.402 %, 0.526 %, 0.263 %, and 0.309 % for B5, B6, B7, and B18 batteries, respectively. …”
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  16. 16
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  17. 17
    A neural network modal decomposition mechanism in predicting network traffic

    A neural network modal decomposition mechanism in predicting network traffic by Shi Jinmei

    Published 2023
    “…Specifically, the predictive accuracy indexes such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) can reach a lowest optimum value of 1.1410, 0.1758 and 0.2263, and the average training time is reduced by 25.25%, 23.87% and 41.36%, respectively. …”
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  18. 18
    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems

    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…The major challenge in the design of Interval type-2 fuzzy logic system (IT2FLS) is to determine the optimal parameters for their antecedent and consequent parts. …”
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  19. 19
    Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system

    Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani

    Published 2022
    “…Furthermore, the SOSDA was applied to optimize the parameters of an interval type-2 fuzzy logic control (IT2FLC) for an inverted pendulum (IP). …”
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  20. 20
    Modification to queueing system M/M/1 with Blum-Blum-Shub generator

    Modification to queueing system M/M/1 with Blum-Blum-Shub generator by Jaffara, M. Z. A. M., Joey, L. F. L.

    Published 2022
    “…In this paper, the researchers modified a type of queueing model simulation which is called ‘M/M/1’ by using a part of Blum-Blum-Shub algorithm. The simulation results reveals that the arrangement of waiting-line is mostly equivalent in graphs, yet there is a difference in the rate interval boundaries. …”
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